Dissertations / Theses on the topic 'Open pit optimization'

Over recent years, new methods have been developed to integrate uncertainty into the optimization of life-of-mine (LOM) production planning. This thesis makes use of two stochastic optimization methods: simulated annealing (SA) and stochastic integer programming (SIP); which are implemented in the context of the requirements of mining applications through the use of stochastic simulation to model uncertainty. For the case of SA, the second chapter of the thesis documents the case of a copper deposit where ten simulated realizations are sufficient to provide stable LOM optimization results. In addition, the study shows that the selected true optimal pit limits are larger than the ones derived through conventional optimization. Stochastically optimized pit limits are found to be about 17% larger, in terms of total tonnage, than the conventional (deterministic) optimal pit limits. The difference adds one year of mining and approximately 10% of additional net present value (NPV) when compared to the NPV of conventional optimal pit limits and a production schedule generated stochastically with the same SA algorithm. In the third chapter of the thesis, the SIP based optimizer is used with the purpose of integrating uncertainty into the process of pushback design. Results show the sensitivity of the NPV to the design of starting and intermediate pushbacks, as well as the pushback design at the bottom of the pit. The new approach yielded an increment of ~30% in the NPV when compared to the conventional approach. The differences reported are due to the different scheduling patterns, the waste mining rate and an extension of the pit limits which yielded an extra ~5.5 thousand tonnes of metal.
Depuis quelques années, de nouvelles méthodes ont été développées pour intégrer l'incertitude dans l'optimisation de la planification de la production de la vie-de-mine i.e. life-of-mine (LOM). Cette thèse se sert de deux méthodes d'optimisation stochastique : recuit simulé (RS) et programmation en nombres entiers stochastique (SIP); les deux méthodes sont programmées dans le cadre des besoins des applications d'exploitation de la simulation stochastique et modélisation d'incertitude. Pour le cas de RS, le deuxième chapitre de la thèse décris le cas d'un dépôt de cuivre où dix réalisations simulées sont suffisantes pour fournir des résultats stables d'optimisation de LOM. En outre, l'étude prouve que les véritables limites optimales choisies de mine sont plus grandes que celles dérivées par l'optimisation conventionnelle. Des limites stochastiquement optimisées de mine s'avèrent environ 17% plus grandes, en termes de tonnage total, que les limites optimales (déterministes) conventionnelles de mine. La différence ajoute un an d'exploitation et approximativement 10% de valeur nette additionnel (NPV) une fois comparée au NPV des limites optimales conventionnelles de mine et une cédule de production produit stochastiquement avec le même algorithme de RS. Dans le troisième chapitre de la thèse, l'optimiseur basé sur SIP est utilisé en vue d'intégration de l'inceritude dans le processus de la conception de fosses emboîtées. Les résultats montrent la sensibilité du NPV à la conception de fosses emboîtées de commencement et intermédiaires aussi bien que la conception de la fosse emboîtée du fond de la mine. La nouvelle approche a produit une augmentation de ~30% dans le NPV une fois comparée à l'approche conventionnelle. Les différences rapportées sont dues aux différents cédules de production, du taux de décapage du stérile et d'une extension des limites de la mine qui ont produit ~5.5 mille tonnes supplémentaires

Open-pit mining is an operation in which blocks from the ground are dug to extract the ore contained in them, and in this process a deeper and deeper pit is formed until the mining operation ends. Mining is often a highly complex industrial operation, with respect to both technological and planning aspects. The latter may involve decisions about which ore to mine and in which order. Furthermore, mining operations are typically capital intensive and long-term, and subject to uncertainties regarding ore grades, future mining costs, and the market prices of the precious metals contained in the ore. Today, most of the high-grade or low-cost ore deposits have already been depleted, and to obtain sufficient profitability in mining operations it is therefore today often a necessity to achieve operational efficiency with respect to both technological and planning issues. In this thesis, we study the open-pit design problem, the open-pit mining scheduling problem, and the open-pit design problem with geological and price uncertainty. These problems give rise to (mixed) discrete optimization models that in real-life settings are large scale and computationally challenging. The open-pit design problem is to find an optimal ultimate contour of the pit, given estimates of ore grades, that are typically obtained from samples in drill holes, estimates of costs for mining and processing ore, and physical constraints on mining precedence and maximal pit slope. As is well known, this problem can be solved as a maximum flow problem in a special network. In a first paper, we show that two well known parametric procedures for finding a sequence of intermediate contours leading to an ultimate one, can be interpreted as Lagrangian dual approaches to certain side-constrained design models. In a second paper, we give an alternative derivation of the maximum flow problem of the design problem. We also study the combined open-pit design and mining scheduling problem, which is the problem of simultaneously finding an ultimate pit contour and the sequence in which the parts of the orebody shall be removed, subject to mining capacity restrictions. The goal is to maximize the discounted net profit during the life-time of the mine. We show in a third paper that the combined problem can also be formulated as a maximum flow problem, if the mining capacity restrictions are relaxed; in this case the network however needs to be time-expanded. In a fourth paper, we provide some suggestions for Lagrangian dual heuristic and time aggregation approaches for the open-pit scheduling problem. Finally, we study the open-pit design problem under uncertainty, which is taken into account by using the concept of conditional value-atrisk. This concept enables us to incorporate a variety of possible uncertainties, especially regarding grades, costs and prices, in the planning process. In real-life situations, the resulting models would however become very computationally challenging.

In this study, dynamic cut-off grades and multiple processing streams are used to maximize the value of a mining project based on a finite resource. Optimal cut-off policies are generated using Lane’s method for determining cut-off grade. By maximizing the present value of future profits as a function of cut-off grade, mine project value is increased over the traditional break-even approach. A method for determining multiple cut-off grades at a single deposit was applied to analyze the impact that changes in processing capacity have on NPV. It was found that additional capacity related to a separate mill facility resulted in an economic reclassification of ore and waste. Grade tonnage data used in the case study was simulated to represent the geologic uncertainty associated to low-grade mineral deposits. Results from the hypothetical case study examined in this thesis reveal that a low-grade open pit gold mine will benefit from the use of multiple processing streams when a dynamic cut-off policy is applied. Particularly, when incorporating a “high grade” modular processing stream to maximize the potential revenue of the mineralized material. This means that for a given set of design, production and geological parameters, the classification of ore and waste is what ultimately determines the NPV of a mining project.
Applied Science, Faculty of
Mining Engineering, Keevil Institute of
Graduate

Modern large-scale open pit mines move hundreds of thousands of tonnes of material daily, from the loading sources to the destination zones, whether these are massive mine dumps or, to a lesser extent, to the grinding mills. Mine dumps can be classified as leach or waste dumps, depending upon their economic viability to be processed in-place, a condition that has experienced great progress in the last decades and has reconfigured the open pit haulage network with an increase in the number of dumps. Therefore, new methods for dump design optimization are of the highest priority in mine planning management. This paper presents a methodology to model and optimize the design of a dump by minimizing the total haulage costs. The location and design of these dumps will be given mainly by the geological characteristics of the mineral, tonnage delivered, topographical conditions, infrastructure capital and transportation costs. Spatial and physical design possibilities, in addition, provide a set of parameters of mathematical and economic relationship that creates opportunities for modelling and thus facilitates the measurement and optimization of ultimate dump designs. The proposed methodology consists of: (1) Formulation of a dump model based on a system of equations relying on multiple relevant parameters; (2) Solves by minimizing the total cost using linear programming and determines a "preliminary" dump design; (3) Through a series of iterations, changes the "preliminary" footprint by projecting it to the topography and creates the ultimate dump design. Finally, an application for a waste rock dump illustrates this methodology.

The mine production schedule defines the sequence of extraction of selected mine units over the life of the mine, and consequentially establishes the ore supply and total material movement. This sequence should be optimized so as to maximize the overall discounted value of the project. Conventional schedule approaches are unable to incorporate grade uncertainty into the scheduling problem formulation and may lead to serious deviations from forecasted production targets. Stochastic mine production schedulers are considered to obtain more robust mine production schedule solutions.
The application of stochastic approaches to the mine production schedule problem is recent and additional testing is required to better understand these tools and to define the value of a stochastic solution as compared to the conventional result. Two stochastic schedulers are tested in a low-grade variability copper deposit, optimization parameters are discussed and their results compared with a conventional schedule.
The first method uses a stochastic combinatorial optimization approach based on simulated annealing to address the mine production schedule problem. The method aims for maximization of the net present value (NPV) of the project and minimization of deviations from the production targets. These objectives are attained by incorporating grade uncertainty into the mine production schedule problem formulation. The second method formulates the problem as a stochastic integer programming problem, in which the objective is the maximization of the projects' NPV and the minimization of production targets deviations. The model can also manage how the risk of deviating from the targets is distributed between production periods.
Both stochastic approaches were tested in a low-grade variability copper deposit. In both case studies, the value of a stochastic solution is demonstrated to be higher than the conventional one. This fact demonstrated the misleading results that a conventional schedule may produce and shows the importance of not ignoring the presence of uncertainty when defining the mine production schedule for a project.

The loading cycle in an Open Pit mine is a critical stage in the production process that needs to be controlled in detail for performance optimization. A comprehensive Alert System designed to notify supervisors of cycle times that are below the required performance standards is proposed. The system gives an alert message when one or several trucks are idle or the time of completing production tasks are over a predefined value. This alert is identified by the system and compared with pre-established Key Performance Indicators (KPIs) in order to determine corrective actions. The goal is to determine the strategies that help the production supervisor to optimize the haulage cycle model. A discrete-event simulator has been built in order to analyze different scenarios for route design and queue analysis. A methodology that utilizes different algorithms has been developed in order to identify the least productive times of the fleet. These results are displayed every time the simulation has finished. This research focuses on the optimization of haulage. However, the system is intended for implementation in subsequent stages of the production process, and the resulting improvement could impact mine planning and management as well. Topographic and drilling exploration data from a mine located hypothetically in the state of Arizona, were used to build a block model and to design an open pit; an Arena-based simulation was used to generate operating cycles that represent actual operations (As-Is model). Once the Alert System is implemented, adjustments were applied, and a new simulation was performed taking into consideration these adjustments (To-Be model), including comparative analysis and statistical results.

Com o passar dos anos a sociedade tem se tornado gradativamente mais dependente de recursos minerais para o seu funcionamento e para o desenvolvimento de produtos. A maior parte das coisas que cercam o homem necessita de alguma espécie de bem mineral como matéria prima para sua fabricação. Por isso, cada vez mais, a mineração tem sido objeto de estudos, buscando aprimoramento e desenvolvimento nos métodos de extração de minérios. Existem duas formas utilizadas para a extração de bens minerais, uma por uso de métodos de lavra a céu aberto (OP) e outra através da aplicação de métodos para lavra subterrânea (UG). A definição de qual método deve ser aplicado em cada caso depende de diversos fatores, como profundidade e geometria do corpo mineral, competência da rocha portadora do minério e da rocha encaixante, entre outros, mas ao final, aspectos econômicos predominam para a definição da viabilidade de cada um dos possíveis métodos. Porém, existem casos em que a melhor escolha para minerar o depósito não se dá por umas dessas duas opções, e sim, pela combinação de ambas, ou seja, a aplicação da lavra a céu aberto seguida da extração dos recursos remanescentes por lavra subterrânea. A grande dificuldade, nestes casos, é definir qual o momento ideal para a transição de método, de maneira que os resultados do projeto integrado sejam otimizados e que um método não inviabilize o outro. Para isso é necessário analisar as duas opções de lavra individualmente, lavrando somente a céu aberto e lavrando somente por métodos subterrâneos, além de analisar-se a viabilidade do projeto através da combinação dos dois métodos, comparando as opções técnica e economicamente e selecionando a que apresente a melhor resposta ao final, para então tomar-se a decisão de qual alternativa de projeto é o mais indicado para cada caso.
Over the years, the society has become progressively dependent on mineral resources for its operation and for development of products. The majority of the things that surround the men needs some kind of mineral material as raw material for its manufacture. Therefore, increasingly, mining has been studied aiming to improve and develop methods of mineral extraction. There are two ways that are utilized to mineral extraction, one by open pit methods (OP) e another by application of underground methods (UG). The definition of which one should be applied in each case depends on many factors, such as depth and geometry of the mineral body, strength of the mineralized and bounding rock, among others, but at the end, economic aspects are predominant for the definition of viability of the methods. However, there are some cases where the best choice to mine the deposit is not one of these options, but the combination of both methods, it means, the application of open pit mining followed by extraction of remaining resources by underground mining. The great challenge, in these cases, is to define what is the right moment for the transition of the methods, making sure that the results are optimized and one method do not impede the development of the other one. In this sense, it is necessary to analyze both options individually, mining the deposit only by open pit and mining only by underground, and also analyze the combination of the two methods, comparing these options technically and economically at the end, and then decide which project alternative is the best for each case.

The building automation industry lacks an affordable, simple, solution for autonomous PID controller tuning when overhead variables fluctuate. In this project, requested by Jitea AB, a solution was developed, utilising step response process modelling, numerical integration of first order differential equations, and Ant Colony Optimization (ACO). The solution was applied to two control schemes; simulated outlet flow from a virtual water tank, and the physical air pressure in the ventilation system of a preschool in Sweden. An open-loop step response provided the transfer function in each case, which, after some manipulation, could be employed to predict the performance of any given set of PID parameters, based on a weighted cost function. This prediction model was used in ACO to find optimal settings. The program was constructed in both Structured Control Language and Structured Text and documented in an approachable way. The results showed that the program was, in both cases, able to eliminate overshoot and retain the settling time (with a slightly raised rise time) achieved with settings tuned per the current methods of Jitea AB. Noise and oscillations present in the physical system did not appear to have any major negative influence on the tuning process. The program performed above Jitea AB’s expectation, and will be tested in more scenarios, as it showed promise. Autonomous implementation could be of societal benefit through increased efficiency and sustainability in a range of processes. In future studies, focus should be on improving the prediction model, and further optimising the ACO variables.
Byggnadsautomationsbranschen saknar en kostnadseffektiv lösning för att autonomt trimma in PID-regulatorer när överordnade variabler fluktuerar. I detta (av Jitea AB beställda) arbete, utvecklades en lösning baserad på stegsvarsmodellering, numerisk integration av första gradens ordinära differentialekvationer och myrkolonisoptimering (ACO). Lösningen applicerades i två regleringsfall; en simulerad utloppsventil från en virtuell vattentank, och det fysiska lufttrycket i ventilationssystemet på en förskola i Sverige. Ett stegsvar med öppen slinga gav en överföringsfunktion i respektive fall, som efter viss manipulering kunde nyttjas för att förutspå prestandan för en uppsättning PID-parametrar baserat på en samlad, viktad kostnadsfunktion. Predikteringsmodellen implementerades i ACO för att finna optimala parametrar. Programmet konstruerades i Structured Control Language och Structured Text, och dokumenterades på ett pedagogiskt sätt. Resultaten visade att programmet (i båda fallen) klarade att eliminera översläng med bibehållen stabiliseringstid (och något förskjuten stigningstid) jämfört med Jitea AB:s existerande trimningsmetod. Signalbrus och oscillationer i det fysiska systemet verkade inte ha någon avsevärd negativ inverkan på trimningsprocessen. Programmet presterade över Jitea AB:s förväntan, och kommer (med tanke på de lovande resultaten) fortsatt att testas i fler scenarion. Implementation av en autonom version skulle kunna innebära flera samhälleliga förmåner i form av ökad verkningsgrad och hållbarhet i en rad processer. I framtida studier bör fokus läggas på att ytterligare förbättra prediktionsmodellen, samt att vidare utforska de optimala myrkolonisvariablerna.

As open pit mines get larger and their road networks more complex, haul road traffic is an area of increasing concern for mine operators. In particular, engineers from Barrick Gold Inc. have observed haul truck interactions in some of their larger open pit mines that are clearly disruptive to the haulage cycle. Such traffic effects cause uncertainty in haul times over identical routes and commercial dispatch systems do not explicitly account for this variability. This research, based on first-hand data collected from the Goldstrike Open Pit in Northern Nevada, focuses on assessing the level of variability in haul times, identifying the sources of said variability, and determining the effects on haulage optimization. Initial data analysis shows different levels of variability over the range of observed haul times, and further investigation identifies certain haulage parameters as significant sources of said variability, such as road topography and intersection effects. Focusing on these areas of interest, relevant data sets were manipulated to reduce levels of data dispersion and compared to observed results in order to quantify the effects in terms of changes to overall mean haul times along identical routes. It was observed that variability has a negative impact on travel times and moderate variability reduction was observed to increase productivity by 1–2 % when used as an input to a simple dispatch simulation program based on the Goldstrike Open Pit.
Thesis (Master, Mining Engineering) -- Queen's University, 2012-08-28 16:02:38.369

Mining operations exploit mineral deposits, processing a portion of the extracted material to produce salable products. The concentration of valuable commodities within these deposits, or the grade, is heterogeneous. Not all material has sufficiently high grades to economically justify processing. Cut-off grade is the lowest grade at which material is considered ore and is processed to create a concentrated commodity product. The choice of cut-off grade at a mining project can be varied over time and dramatically impacts both the operation of the mine and the economics of the project. The majority of literature and the accepted industry practices focus on optimizing cut-off grade under known commodity prices. However, most mining operations sell their products into highly competitive global markets, which exhibit volatile commodity prices. Making planning decisions assuming that a given commodity price prediction is accurate can lead to sub-optimal cut-off grade strategies and inaccurate valuations. Some academic investigations have been conducted to optimize cut-off grade under stochastic or uncertain price conditions. These works made large simplifications in order to facilitate the computation of a solution. These simplifications mean that detailed mine planning data cannot be used and the complexities involved in many real world projects cannot be considered. A new method for optimizing cut-off grade under stochastic or uncertain prices is outlined and demonstrated. The model presented makes use of theory from the field of Real Options and is designed to incorporate real mine planning data. The model introduces two key innovations. The first is the method in which it handles the cut-off grade determination. The second innovation is the use of a stochastic price model of the entire futures curve and not simply a stocastic spot price model. The model is applied to two cases. The first uses public data from a National Instrument 43-101 report. The second case uses highly detailed, confidential data, provided by a mining company from one of their operating mines.
Thesis (Master, Mining Engineering) -- Queen's University, 2012-04-30 22:36:51.257

Detailed geological knowledge is often a major unknown factor in open pit mining and design, and therefore poses a significant risk in the mining venture. As the knowledge of the geology improves so the risk of unforeseen conditions reduces and therefore safety and productivity can be increased. Historically, geotechnical methods and information have predominantly been used exclusively for pit slope optimisation. This research documents the procedures and developments undertaken to compile a comprehensive geotechnical database, and the application of the geotechnical data to open pit mining, beneficiation and planning. The utilisation of the geotechnical information has been enhanced through the novel development and application of a computerised, 3D geotechnical model. Sandsloot open pit was developed to extract the Platreef pyroxenite orebody, which is hosted within the Northern Limb of the Bushveld Complex. Sandsloot is currently the world's largest open pit exploiting Platinum Group Metals. Interaction of the basic magma with the footwall sediments of the Transvaal Supergroup and varying degrees of assimilation has resulted in a unique suite of hybrid rock types. These various rock types provide significant engineering geological challenges. Geology and the detailed understanding of its properties are fundamental to the optimal design and successful operation of any mine. Extensive fieldwork was conducted to collect geotechnical information, both from exploration boreholes and in-pit mining faces. Over a 5-year period, geotechnical data were collected from 29,213 m of exploration core and 6,873 m of exposed mining faces. Extensive field and laboratory testing was undertaken in order to define the complete set of geotechnical properties for each rock type in the Sandsloot mining area. The geotechnical information relating to each borehole and facemap was stored in the Datamine® software package. The information was collected in the form of rock mass rating (RMR), uniaxial compressive strength (DCS), fracture frequency (FF/m) and rock quality designation (RQD). The architecture of the database was developed along the principals used for generating an ore reserve model. One of the novel applications was the development of a computerized 3D, geotechnical model in Datamine®. The geotechnical parameters, namely RMR, DCS, FF/m and RQD, were modelled for each rock type, using geostatistics, to generate a 3D model. The data were interpolated between exploration boreholes and exposed mining faces and the modelling was constrained using wireframes separated by rock type. The result is a 3D model containing 15 m3 model blocks populated with interpolated geotechnical information. The dimensions of the model blocks are linked to the mining bench height of 15 m. The model can be queried to give predictions on rock mass conditions for any planned mining area, as is the case with the ore reserve model, which provides predictions on platinum grades. The crux of the innovative research is the practical application of the 3D geotechnical model. This was achieved through the development of both a fragmentation and a slope design model, which read the interpolated geotechnical information. These models provided an engineering tool to optimise mining and milling perfonnance. Rather than viewing the drill and blast department as an isolated cost centre and focussing on minimising drill and blast costs, the application of the model concentrated on the fragmentation requirements of the milling and mining business areas. Two hundred and thirty-eight blasts were assessed to detennine the optimum fragmentation requirements for ore and waste. Based on the study a mean fragmentation target of 150 mm was set for delivery to the crushing circuit and a mean fragmentation of 230 mm was set for waste loading from the pit. The mine operates autogenous mills, which are sensitive to the fragmentation profile delivered. The harder zones occurring in the ore zone have a major impact on the plant's perfonnance. The geotechnical parameters in the model were related to Lilly's Blastability Index, and in turn to required explosive volumes and the associated drill and blast costs. Having defmed the fragmentation targets, the Kuz-Ram equation was used in the fragmentation model to predict the explosive volumes required to ensure consistent mining and milling perfonnance. The geotechnical model is used to predict changes in geotechnical conditions and therefore the blasting parameters can be adjusted in advance to ensure the milling and mining fragmentation requirements are met. Through the application of the fragmentation model over an eighteen-month period the loading and milling efficiencies improved by 8.5% and 8.8% respectively, resulting in additional revenue ofR29 million for PPL. Based on the mining rock mass rating (MRMR) values within the geotechnical model a stable slope design model was created in order to calculate optimum inter-ramp angles. From a slope design perspective the model was used to target data-deficient zones and highlight potentially weak rock mass areas. As this can be viewed in 3D, the open pit slopes were designed to accommodate the poor quality areas before they are excavated. It also follows that competent geotechnical zones can be readily identified and the slope optimised accordingly. Due to the detailed geotechnical infonnation being available in three dimensions, the open pit slopes were designed based on a risk versus reward profile. As a significant geotechnical database was available, more accurate and reliable designs were generated resulting in the overall slope angle increasing by 3 degrees. This optimisation process will result in a revenue gain of R900 million over the life of the mine. The revenue and safety benefits associated with this design methodology are substantial and have potential application to all open pit mining operations. The research has enabled detailed geotechnical infonnation to be available in three dimensions. This information can be readily accessed and interpreted, thus providing a powerful planning and financial tool from which production optimisations, feasibility studies and planning initiatives can be implemented. The development and application of a 3D geotechnical model has added a new dimension to the constant strive for business improvement and reflects a novel and successful approach towards the application of engineering geology at the Sandsloot mining operation.
Thesis (Ph.D.)-University of Natal, Durban, 2003.

Dissertação de Mestrado em Geociências apresentada à Faculdade de Ciências e Tecnologia
A área em estudo localiza-se no municipio de Baucau, Timor-Leste. O Municipio de Baucau confina com o municipio de Lautem a este, com o Manatutu a oeste, com o de Viqueque a sul e com o estreito de Wetar a norte. Fica a aproximadamente 120km a este de Dili, a capital da República de Timor Leste. As áreas concessionadas são referidas por Bloco I-1, Bloco I-2, e Bloco II.Para o calcário de Baucau na área de concessão no bloco I-Mina1 e Mina2, a modelação e a estimativa de recursos são ferramentas críticas para o desenvolvimento desta área de concessão. Assim, o calcário é uma das matérias-primas importantes para a produção de cimento, sendo também necessário gesso, sílica e argila como materiais complementares. O cimento é um dos materiais importantes para o desenvolvimento como nação, especialmente para Timor-Leste no presente e no futuro. Os teores médios de CaO variam entre 42-53% no bloco I-Mina1 e entre 54-55% no bloco I-Mina2. As litologias encontradas na área de concessão são diversas, como solo superior, calcário recifal, calcário arenoso, calcário macio e argila. A modelação permitiu calcular valores máximo das percentagens da composição química (Al2O3, CaO, Cl, Fe2O3, MgO e K2O). Existem vários modelos médios, nomeadamente o modelo Al2O3, modelo CaO, modelo SiO2 e modelo Fe2O3. Indice de hidraulicidade, módulo de sílica, modulo férrico de alumínio e módulo de saturação de cal. A estimativa de recursos no bloco I-Mina1 e no bloco Mina2 seguiu as recomendações do Código JORC.
The study area is located in the Baucau Municipality, East Timor. Baucau Municipality borders with Lautem Municipality in the east, with Manatutu Municipality in the west, with Viqueque Municipality in the south and with the strait of Wetar in the north, it is approximately 120 km east of Dili, capital of Democratic Republic of Timor Leste. The mineral licenses areas consist of Block I-1, Block I-2 and Block II.For the Baucau Limestone at concession area in block I-Mine1 and Mine2, the modelling and resources estimation is a critical tool for the development of that concession area. Thus, limestone is one of the important raw materials needed for producing cement while gypsum, silica and clay are needed as a complimentary materials. Cement is one of the important materials necessary for for the development of the nation especially for Timor-Leste in the present and in the future. There average grades of CaO vary from 42 to 53% at block I-Mine1 and from 54 to 55% for block I-Mine2. The lithologies found in the concession area are diverse such as top soil, coral reef limestone, sandy limestone, chalky or soft limestone and clay. The modelling permitted to calculate maximum of the percentages of the chemical composition that consist of Al2O3, CaO, Cl, Fe2O3, MgO and K2O. There are various average models namely Al2O3 model, CaO model, SiO2 model and Fe2O3 model. Index hydraulicity, silica module, aluminum ferric module and lime saturation module. The estimated resources at block I-Mine1 and Mine2 follow the recommendations of the JORC Code reporting standardization.